摘要
太阳能光伏发电中,组件的发电效率成为影响发电量的关键因素。光伏组件中存在的隐裂等各种缺陷对其效率带来了很多不利影响。从微缺陷光伏组件出发,在已有研究成果上,提出了一种使用MATLAB的图像处理工具箱来智能分类缺陷组件并确定缺陷位置的方法。主要分为四个模块,分别从图像处理总路线、智能定位缺陷方法、智能分类缺陷组件方法和实例验证的角度阐述了MATLAB模型的建立与验证过程。这一研究成果可以大大提高光伏组件检测的效率和准确性,有很重要的实际应用意义。
In solar photovoltaic power generation, the power generation efficiency of modules becomes the key factor affecting the power generation. The hidden cracks and other defects in the photovoltaic module have brought many adverse effects on its efficiency. Based on the existing research results, a method of using MATLAB image processing toolbox to classify defect modules intelligently and determine the location of defects was proposed. This paper was mainly divided into four parts, image processing general route, intelligent locating defects methods, intelligent classification of defect modules methods and example verification, to demonstrate the establishment and verification process of MATLAB model. The efficiency and accuracy of detection of photovoltaic modules were greatly improved, and it was with very important practical significance.
作者
戴磊
张臻
黄恒敬
敖翔
DAI Lei;ZHANG Zhen;HUANG Heng-jing;AO Xiang(The College of Mechanical and Electrical Engineering, Hohai University, Changzhou Jiangsu 213022, China)
出处
《电源技术》
CAS
北大核心
2019年第8期1359-1362,共4页
Chinese Journal of Power Sources
基金
江苏省自然科学基金(BK20151173)
关键词
电致发光
图像识别
缺陷分类
缺陷定位
electroluminescence
image recognition
defect classification
defect locating
